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17 pages, 1243 KiB

Open AccessArticle

Modeling Occurrence of Urban Mosquitos Based on Land Use Types and Meteorological Factors in Korea

by Yong-Su Kwon, Mi-Jung Bae, Namil Chung, Yeo-Rang Lee, Suntae Hwang, Sang-Ae Kim, Young Jean Choi and Young-Seuk Park

Int. J. Environ. Res. Public Health 2015, 12(10), 13131-13147; https://doi.org/10.3390/ijerph121013131 - 20 Oct 2015

Cited by 5 | Viewed by 5656

Abstract

Mosquitoes are a public health concern because they are vectors of pathogen, which cause human-related diseases. It is well known that the occurrence of mosquitoes is highly influenced by meteorological conditions (e.g., temperature and precipitation) and land use, but there are insufficient studies quantifying their impacts. Therefore, three analytical methods were applied to determine the relationships between urban mosquito occurrence, land use type, and meteorological factors: cluster analysis based on land use types; principal component analysis (PCA) based on mosquito occurrence; and three prediction models, support vector machine (SVM), classification and regression tree (CART), and random forest (RF). We used mosquito data collected at 12 sites from 2011 to 2012. Mosquito abundance was highest from August to September in both years. The monitoring sites were differentiated into three clusters based on differences in land use type such as culture and sport areas, inland water, artificial grasslands, and traffic areas. These clusters were well reflected in PCA ordinations, indicating that mosquito occurrence was highly influenced by land use types. Lastly, the RF represented the highest predictive power for mosquito occurrence and temperature-related factors were the most influential. Our study will contribute to effective control and management of mosquito occurrences. Full article

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25 pages, 2200 KiB

Open AccessArticle

Response of Fish Communities to Various Environmental Variables across Multiple Spatial Scales

by Yong-Su Kwon, Fengqing Li, Namil Chung, Mi-Jung Bae, Soon-Jin Hwang, Myeong-Seop Byoen, Sang-Jung Park and Young-Seuk Park

Int. J. Environ. Res. Public Health 2012, 9(10), 3629-3653; https://doi.org/10.3390/ijerph9103629 - 15 Oct 2012

Cited by 24 | Viewed by 8843

Abstract

A better understanding of the relative importance of different spatial scale determinants on fish communities will eventually increase the accuracy and precision of their bioassessments. Many studies have described the influence of environmental variables on fish communities on multiple spatial scales. However, there is very limited information available on this topic for the East Asian monsoon region, including Korea. In this study, we evaluated the relationship between fish communities and environmental variables at multiple spatial scales using self-organizing map (SOM), random forest, and theoretical path models. The SOM explored differences among fish communities, reflecting environmental gradients, such as a longitudinal gradient from upstream to downstream, and differences in land cover types and water quality. The random forest model for predicting fish community patterns that used all 14 environmental variables was more powerful than a model using any single variable or other combination of environmental variables, and the random forest model was effective at predicting the occurrence of species and evaluating the contribution of environmental variables to that prediction. The theoretical path model described the responses of different species to their environment at multiple spatial scales, showing the importance of altitude, forest, and water quality factors to fish assemblages. Full article

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